The field of the invention relates to systems and methods for ionizing radiation treatment. More particularly, the invention relates to systems and methods for improved proton therapy.
Proton therapy systems takes advantage of the energy deposition profile of high energy protons in tissue to provide highly conformal exposure of tumors while sparing critical structures. Specifically, protons have a finite penetration depth in dependence of their energy, as shown in FIG. 1A. In contrast to a photon beam 100 in conventional radiotherapy, the radiation dose delivered by a mono-energetic proton beam 102 is maximal within a short distance of a proton's end range in tissue, known as the Bragg peak 104. Superficial tissues receives less radiation dose compared to those at the Bragg peak. In addition, the dose profile drops dramatically beyond the Bragg peak, with tissues receiving practically no radiation dose thereafter. Such dose deposition characteristics allows high doses to be delivered to deep-seated tumors while reducing normal tissue doses and toxicities.
To provide volume coverage to a target 106, often a combination 108 of multiple proton beams with different energies are utilized, resulting in a spread-out Bragg peak 110. However, this comes at the cost of increased superficial tissue doses, as appreciated form FIG. 1A. Regardless of whether single or multi-energy beams are used, due to the steep dose drop-off near the Bragg peak, proton range errors are often of concern. This is especially important when critical structures are located just beyond the target 106. As such, range inaccuracy could result increased toxicities due to critical structures receiving close to a full dose, or tumors receiving suboptimal coverage.
During proton therapy, positron emitting radionuclides, such as 15-O, 13-N and 11-C, are produced through nuclear fragmentation reactions. Therefore, positron emission tomography (PET) imaging of the activity distribution of these proton induced positron emitters has emerged as a possible approach for in vivo proton therapy verification. Specifically, the spatial distribution of the produced positron emitters is related to proton fluence, nuclear reaction cross-sections and target nuclide concentration distributions. As such, local intensities of PET images obtained after treatment can identify the extent of the irradiated tissue and some kind of distal activity threshold can help define proton beam range errors.
However, as shown in FIG. 1B, PET activity as a function of depth differs from the dose distribution, since these are produced through very different physical processes. Therefore, any verification of a proton treatment plan and beam delivery must be carried out indirectly. To do this, current approaches generate production maps of different radionuclide species by performing Monte Carlo (MC) simulations based on treatment planning information and tissue composition maps obtained from CT images. However, in addition to radioactive decay, biological processes complicate the prediction of deposited dose, beam range, and radioactivity because simple analysis of PET image intensities do not distinguish between biological washout and an absence of dose deposition. In particular, it is known that biological washout can dramatically change the original proton induced activity distribution, particularly in soft tissues. Therefore, production maps are often corrected for radioactive decay and biological washout to generate a predicted PET activity distribution.
In one previous approach, correction of the production maps utilizes a model that includes nominal values for biological clearance applied retrospectively to the MC data. Specifically, thresholds on the treatment-CT image numbers are set to identify fat, soft tissue, bone, cortical bone, muscle and brain tissues. The washout in each tissue type is then decomposed into three components, namely fast, medium and slow. Fractions and biological half-lives are assigned to each component in each tissue type, based on animal study results with stable and radioactive carbon ion beams. After applying radioactive decay corrections and predefined nominal biological washout corrections, distributions from different radionuclides are then summed to form predicted PET activity distributions, which are then compared with static PET images.
This approach has several limitations that prevents accurate verification of proton therapy. First, model parameters adopted above are from carbon-beam studies, making their applicability to proton beam therapy questionable. This is because projectile fragmentation is more important in carbon ion therapy, while only target fragmentation is possible in proton therapy. That is, in carbon beam therapy, 11-C obtained from projectile fragmentation is the dominant radionuclide, while in proton therapy, 15-O obtained from target fragmentations reactions has the highest yield. Second, the approach above does not account for varied washout rates of radionuclides incorporated as different molecular species. In fact, the CT number is insufficient to fully characterize the tissue environment, since the chemical form of a product determines its biological fate. Third, biological clearance is greatly affected by the prevailing biological environment, such as local vascular development, tissue heterogeneity and perfusion rate, not to mention prior chemotherapy or radiation treatment. As such, clinical studies have shown that biological washout was one of the major reasons for the discrepancies between the measured and simulated ranges when the proton beam stops in soft tissue.
Hence, there is a need for systems and methods for use in identifying and mitigating errors in order to deliver precise and predictable proton therapy with the highest clinical benefit.